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Updated: Nov 20, 2025
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Brief international cognitive assessment for multiple sclerosis (BICAMS) cut-off scores for detecting cognitive
Artemios Artemiadis1, Christos Bakirtzis2, Andreas Chatzittofis3
1Medical School, University of Cyprus, Old Road Nikosia-Limmasol 215/6, 2029 Aglantzia, Nicosia, Cyprus; Department of Neurology, Army Share Fund Hospital (NIMTS), Monis Petraki 10, 11521, Athens, Greece.
Background:
Cognitive impairment (CI) affects 35-65% of multiple sclerosis (MS) patients. The Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) has been proposed as a highly feasible and cost-effective tool for cognitive impairment (CI) screening in MS. The tool yields scores that should, ideally, readily convey patients' cognitive status to the clinicians.
Methods:
To this aim, this study sought for cut-off scores of the three BICAMS test in a sample of 960 MS patients. We used three definitions for CI: 1.5, 1,65 and 2 standard deviations below the mean. Receiver operating characteristic (ROC) statistics helped us determine the capacity of BICAMS to diagnose CI. Optimal cut-offs were determined by the delta distance. Positive and negative predictive values, along with overall accuracy were also calculated.
Results:
Symbol Digit Modalities Test (SDMT) and California Verbal Learning Test-II (CVLT-II) showed a diagnostic accuracy ranging from 74.6 to 77.4%, across the three CI definitions. The accuracy of Brief Visuospatial Memory Test-Revised (BVMT-R) was over 88%. SDMT had a balanced sensitivity, while CVLT-II and BVMT-R had higher specificities than sensitivities at detecting CI. More specifically, BVMT-R showed 100% specificity for all CI definitions. Raw cut-off scores for BICAMS tests are also provided within the manuscript, along with the diagnostic calculations.
Conclusions:
In this study, we confirmed that BICAMS is a good screening tool for CI and that simple cut-offs can be used in the everyday neurological practice.
Insights
The Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) effectively screens for cognitive impairment in MS patients. This study provides simple cut-off scores for clinical use, enhancing diagnostic accuracy.
Area of Science:
- Neurology
- Neuropsychology
- Clinical Neuroscience
Background:
- Cognitive impairment (CI) affects a significant portion of multiple sclerosis (MS) patients.
- The Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) is a proposed tool for CI screening in MS.
- Clinicians need readily interpretable scores to assess patients' cognitive status.
Purpose of the Study:
- Determine optimal cut-off scores for BICAMS tests in MS patients.
- Evaluate the diagnostic capacity of BICAMS for CI using various definitions.
- Provide practical cut-off values for routine neurological practice.
Main Methods:
- Analyzed data from 960 MS patients.
- Utilized three definitions for CI (1.5, 1.65, and 2 standard deviations below the mean).
- Employed Receiver Operating Characteristic (ROC) statistics and delta distance for optimal cut-off determination.
Main Results:
- The Symbol Digit Modalities Test (SDMT) and California Verbal Learning Test-II (CVLT-II) demonstrated diagnostic accuracies between 74.6% and 77.4%.
- The Brief Visuospatial Memory Test-Revised (BVMT-R) achieved over 88% accuracy.
- BVMT-R exhibited 100% specificity for all CI definitions, while SDMT offered balanced sensitivity.
Conclusions:
- BICAMS is a validated and effective screening tool for CI in MS.
- Simple cut-off scores derived from this study can be implemented in clinical practice.
- The findings support the routine use of BICAMS for cognitive assessment in MS patients.
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